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Journal ArticleDOI

Applications of Structural Equation Modeling in Psychological Research

Robert C. MacCallum, +1 more
- 01 Jan 2000 - 
- Vol. 51, Iss: 1, pp 201-226
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TLDR
This chapter presents a review of applications of structural equation modeling (SEM) published in psychological research journals in recent years and focuses first on the variety of research designs and substantive issues to which SEM can be applied productively.
Abstract
This chapter presents a review of applications of structural equation modeling (SEM) published in psychological research journals in recent years. We focus first on the variety of research designs and substantive issues to which SEM can be applied productively. We then discuss a number of methodological problems and issues of concern that characterize some of this literature. Although it is clear that SEM is a powerful tool that is being used to great benefit in psychological research, it is also clear that the applied SEM literature is characterized by some chronic problems and that this literature can be considerably improved by greater attention to these issues.

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TL;DR: In this article, the authors present a detailed, worked-through example drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology.
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A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example

TL;DR: What factorial validity is and how to run its various aspects in PLS are explained and an annotated example with data is provided to assist in reconstructing the detailed example.
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Validation guidelines for is positivist research

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An introduction to latent class growth analysis and growth mixture modeling.

TL;DR: The authors provide an overview of latent class and growth mixture modeling techniques for applications in the social and psychological sciences, discuss current debates and issues, and provide readers with a practical guide for conducting LCGA and GMM using the Mplus software.
References
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Journal ArticleDOI

Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives

TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Book

Principles and Practice of Structural Equation Modeling

TL;DR: The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
Journal ArticleDOI

Alternative Ways of Assessing Model Fit

TL;DR: In this paper, two types of error involved in fitting a model are considered, error of approximation and error of fit, where the first involves the fit of the model, and the second involves the model's shape.
Book

Structural Equations with Latent Variables

TL;DR: The General Model, Part I: Latent Variable and Measurement Models Combined, Part II: Extensions, Part III: Extensions and Part IV: Confirmatory Factor Analysis as discussed by the authors.
Journal ArticleDOI

Significance tests and goodness of fit in the analysis of covariance structures

TL;DR: In this article, a general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models, and the importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models.
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